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رشته نرم افزار کامپیوتر
دانشکده فنی پسران بیرجند
01 دی 1395 - Now
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ارشد نرم افزار
22 آذر 1394
گرایش مدیریت داده، دانشگاه اصفهان، معدل 17.87
لیسانس نرم افزار
30 شهریور 1390
دانشگاه بیرجند، معدل 18.33
فوق دیپلم کامپیوتر
09 تیر 1389
دانشکده فنی و حرفه‌ای پسران بیرجند، معدل 17.90
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مقاله
01 اسفند 1395
Abstract The aim of this paper is to propose an efficient method for identification of web document topics which is often considered as one of the debatable challenges in many information retrieval systems. Most of the previous works have focused on analyzing the entire text using time-consuming methods and also many of them have used unsupervised approaches to identify the main topic of documents. However, in this paper, it is attempted to exploit the most widely-used Hyper-Text Markup Language (HTML) features to extract topics from web documents using a supervised approach. Hiring an interactive crawler, we firstly try to analyze HTML structures of 5000 webpages in order to identify the most widely-used HTML features. In the next step, the selected features of 1500 webpages are extracted using the same crawler. Suitable topics are given to each web document by users in a …
مقاله
02 مرداد 1394
It will not take a longtime that the human will apply the networks of sensors in controlling the environment and predict natural disasters. This vast function would create bulks of sensor data to be applied World Wide Web. These bulks of data should be handled and processed a primary manner, which is a difficult task; therefore only the expert in this field can process them. One solution to overcome this drawback is the application of Open Geospatial Consortium (OGC) standard which to the sensor networks would develop the concept of sensor web; hence access to the sensor observations through the web. Data semantic is prerequisite of this process. To overcome this drawback the combination of sensor web and semantic web technology that constitutes the new concept named semantic sensor web should be adopted. The objective of this article is to develop a semantic sensor web
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